Machine learning and deep learning based computational techniques in automatic agricultural diseases detection: Methodologies, applications, and challenges
Plant disease detection is a critical issue that needs to be focused on for productive
agriculture and economy. Detecting plant disease using traditional methods is a tedious job …
agriculture and economy. Detecting plant disease using traditional methods is a tedious job …
Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations
Accurate and rapid plant disease detection is critical for enhancing long-term agricultural
yield. Disease infection poses the most significant challenge in crop production, potentially …
yield. Disease infection poses the most significant challenge in crop production, potentially …
A precise image-based tomato leaf disease detection approach using PLPNet
Z Tang, X He, G Zhou, A Chen, Y Wang, L Li… - Plant Phenomics, 2023 - spj.science.org
Tomato leaf diseases have a significant impact on tomato cultivation modernization. Object
detection is an important technique for disease prevention since it may collect reliable …
detection is an important technique for disease prevention since it may collect reliable …
Automated real-time identification of medicinal plants species in natural environment using deep learning models—a case study from Borneo Region
The identification of plant species is fundamental for the effective study and management of
biodiversity. In a manual identification process, different characteristics of plants are …
biodiversity. In a manual identification process, different characteristics of plants are …
An ensemble deep learning models approach using image analysis for cotton crop classification in AI-enabled smart agriculture
MF Shahid, TJS Khanzada, MA Aslam, S Hussain… - Plant methods, 2024 - Springer
Background Agriculture is one of the most crucial assets of any country, as it brings
prosperity by alleviating poverty, food shortages, unemployment, and economic instability …
prosperity by alleviating poverty, food shortages, unemployment, and economic instability …
Tomato spotted wilt disease severity levels detection: a deep learning methodology
V Salonki, A Baliyan, V Kukreja… - 2021 8th International …, 2021 - ieeexplore.ieee.org
The wide variety of diseases in the tomato plant affects the quality and quantity of the
production. To counteract the problem of disease in tomato plants deep learning (DL) based …
production. To counteract the problem of disease in tomato plants deep learning (DL) based …
Computer vision framework for wheat disease identification and classification using Jetson GPU infrastructure
Diseases have adverse effects on crop production and yield loss. Various diseases such as
leaf rust, stem rust, and strip rust can affect yield quality and quantity for a studied area. In …
leaf rust, stem rust, and strip rust can affect yield quality and quantity for a studied area. In …
Feature fusion and kernel selective in Inception-v4 network
F Chen, J Wei, B Xue, M Zhang - Applied Soft Computing, 2022 - Elsevier
In recent years, deep learning has been developed very quickly, and related research has
shown a blossoming scene. Inception-v4 is a wide and deep network with good …
shown a blossoming scene. Inception-v4 is a wide and deep network with good …
Dronesegnet: robust aerial semantic segmentation for UAV-based IoT applications
Unmanned Aerial Vehicles (UAVs) are the promising “Flying IoT” devices of the future, which
can be equipped with various sensors and cognitive capabilities to perform numerous tasks …
can be equipped with various sensors and cognitive capabilities to perform numerous tasks …
Application of YOLO and ResNet in heat staking process inspection
H Jung, J Rhee - Sustainability, 2022 - mdpi.com
In the automobile manufacturing industry, inspecting the quality of heat staking points in a
door trim involves significant labor, leading to human errors and increased costs. Artificial …
door trim involves significant labor, leading to human errors and increased costs. Artificial …